Product Manager, Relevance and Personalization

Airbnb is a global marketplace connecting guests with unique stays and experiences offered by hosts worldwide. The Product Manager for Relevance & Personalization will set strategy and drive execution for AI-powered relevance, search, recommendation, and personalization systems, owning the roadmap and partnering with technical and cross-functional teams to improve guest and host outcomes at global scale.

Responsibilities:

• Define and drive the roadmap for Airbnb's relevance and personalization platform — from natural language query understanding to multi-turn, context-aware discovery experiences
• Make prioritization calls that balance multiple competing objectives: guest experience, host success, revenue, fairness, and marketplace health
• Partner with ML engineers and applied researchers to shape model strategy, evaluation frameworks, and experimentation design
• Align cross-functional partners — Guest, Host, MarTech, Trust & Safety, Customer Support — on shared goals and sequencing
• Drive the Tripcycle vision: ensuring R&P's intelligence layer connects across the full trip lifecycle, from inspiration through post-trip
• Design and oversee A/B experiments with rigorous metric design and long-term effect measurement
• Translate complex technical tradeoffs into clear decisions for engineering teams and concise narratives for leadership
• Foster an environment where engineers and product managers collaborate on building the future
• Stay close to guests and hosts: synthesize user research, marketplace data, and competitive signals to sharpen your intuition and refine strategy

Requirements:

• 10+ years of product management experience, with at least 3 years on ML, search, recommendations, or AI-powered products at scale
• Track record of owning strategy and roadmap for technically complex systems — not just managing features, but setting direction and making hard prioritization calls
• Strong experimentation fluency: comfortable designing A/B tests, interpreting counterfactual results, and reasoning about proxy metrics vs. long-term outcomes
• Experience working on two-sided marketplaces or platforms where you balanced supply-side and demand-side tradeoffs
• Ability to earn the respect of Staff and Principal-level engineers and researchers — you don't need to write code, but you need to engage at a level that builds credibility
• Clear, structured communicator who can distill complex technical tradeoffs for executives and translate strategic intent into actionable guidance for engineers
• Due to the nature of this position, there is a strong preference for the successful applicant will need to be based in San Francisco, CA to be able to conduct their work
• Currently, employees can not be located in: Alaska, Indiana, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin, Alabama, Mississippi, Oklahoma, Delaware And Rhode Island
• Experience with LLM-based products in production — ideally involving evaluation challenges, latency constraints, or safety and guardrail work (preferred)
• Familiarity with reinforcement learning, contextual bandits, or explore/exploit frameworks in a product context (preferred)
• Background working alongside applied researchers or with teams that publish externally (preferred)